Profound Impact is proud to sponsor the 2023 CS-Can|Info-Can Outstanding Early Career Computer Science Researcher Awards. The awards will be presented at the Second CS-Can|Info-Can Conference Co-Located with CASCON, November 11-14 at York University in Toronto. Congratulations to all three winners!

Roger Grosse of University of Toronto

Dr. Roger Grosse is an Associate Professor in the Department of Computer Science at the University of Toronto. With a robust research focus on machine learning and artificial intelligence, Dr. Grosse’s work explores innovative approaches to learning algorithms and their applications. His research interests span topics such as neural network training, probabilistic models, and scalable learning methods.

Dr. Grosse holds a Ph.D. from the University of Cambridge and has contributed significantly to the field through numerous publications and collaborations. His work is instrumental in advancing our understanding of complex machine-learning systems and their practical implementations.

As a leading researcher, Dr. Grosse is committed to pushing the boundaries of what is possible with machine learning technologies, making impactful contributions to both academia and industry.

Ali Ouni of ETS Montréal 

Dr. Ali Ouni is a Professor at École de Technologie Supérieure (ETS) in Montréal, specializing in computer vision and machine learning. His research focuses on developing advanced algorithms for visual perception, object recognition, and scene understanding.

Dr. Ouni’s work is pivotal in the fields of computer vision and artificial intelligence, where he explores innovative techniques to improve visual data analysis and interpretation. His contributions aim to enhance the capabilities of machine learning systems in understanding and interacting with visual information.

With a robust academic background and a strong track record of research, Dr. Ouni is dedicated to advancing the state of the art in computer vision and its applications, driving progress in both academic and practical contexts.

Liam Paull of Université de Montréal

Dr. Liam Paull is an Associate Professor in the Department of Computer Science and Operations Research at the Université de Montréal. His research focuses on robotics, artificial intelligence, and machine learning, with a particular emphasis on developing algorithms that enable robots to perceive and interact with complex environments.

Dr. Paull’s work explores areas such as autonomous systems, robot perception, and human-robot interaction. He is dedicated to advancing the field of robotics through innovative research and applications that address real-world challenges.

With a strong academic background and a commitment to impactful research, Dr. Paull is shaping the future of robotics and AI, contributing valuable insights and technological advancements to the field.